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README.md

@@ -1,14 +1,36 @@
 ---
-title: Fooocus Pro
-emoji: 👀
-colorFrom: gray
+title: Fooocus Web
+emoji: 🎨
+colorFrom: purple
 colorTo: indigo
 sdk: gradio
-sdk_version: 5.12.0
+sdk_version: 4.19.2
 app_file: app.py
 pinned: false
-license: apache-2.0
-short_description: Fooocus pro presents a rethinking of image generator designs
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Fooocus Web
+
+A web interface for Fooocus, the powerful Stable Diffusion image generation tool.
+
+## Features
+
+- High-quality image generation
+- Advanced prompt processing
+- Multiple styles and presets
+- Negative prompts support
+- Advanced sampling methods
+- Refiner integration
+
+## Usage
+
+1. Enter your prompt in the text box
+2. Adjust the settings as needed
+3. Click "Generate" to create your image
+4. Use advanced features for more control
+
+## Parameters
+
+- **Style**: Choose from various preset styles
+- **Performance**: Balance between quality and speed
+- **Advanced**: Fine-tune the generation process

app.py

@@ -0,0 +1,200 @@
+import os
+import gradio as gr
+import torch
+from diffusers import StableDiffusionXLPipeline, EulerDiscreteScheduler
+from safetensors.torch import load_file
+
+# Constants
+MODEL_ID = "stabilityai/stable-diffusion-xl-base-1.0"
+REFINER_MODEL_ID = "stabilityai/stable-diffusion-xl-refiner-1.0"
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+DTYPE = torch.float16 if torch.cuda.is_available() else torch.float32
+
+class FooocusGenerator:
+    def __init__(self):
+        self.pipe = None
+        self.refiner = None
+        self.load_models()
+
+    def load_models(self):
+        # Load base model
+        scheduler = EulerDiscreteScheduler.from_pretrained(MODEL_ID, subfolder="scheduler")
+        self.pipe = StableDiffusionXLPipeline.from_pretrained(
+            MODEL_ID,
+            scheduler=scheduler,
+            torch_dtype=DTYPE,
+            use_safetensors=True,
+            variant="fp16" if DEVICE == "cuda" else None
+        )
+        
+        if DEVICE == "cuda":
+            self.pipe.enable_xformers_memory_efficient_attention()
+        self.pipe.to(DEVICE)
+
+    def generate_image(
+        self,
+        prompt,
+        negative_prompt,
+        style_selections,
+        performance_selection,
+        aspect_ratios_selection,
+        image_number,
+        image_seed,
+        sharpness,
+        guidance_scale,
+        base_model_name,
+        refiner_model_name,
+        progress=gr.Progress()
+    ):
+        try:
+            # Process style selections
+            processed_prompt = self.process_style(prompt, style_selections)
+            
+            # Generate the image
+            generator = torch.Generator(device=DEVICE).manual_seed(image_seed)
+            
+            image = self.pipe(
+                prompt=processed_prompt,
+                negative_prompt=negative_prompt,
+                num_inference_steps=30,
+                guidance_scale=guidance_scale,
+                generator=generator,
+            ).images[0]
+            
+            return image
+            
+        except Exception as e:
+            print(f"Error generating image: {str(e)}")
+            return None
+
+    def process_style(self, prompt, style_selections):
+        # Add style modifiers to the prompt
+        style_modifiers = {
+            "Fooocus V2": ", professional, high quality, detailed",
+            "Fooocus Enhance": ", enhanced details, perfect composition",
+            "Fooocus Sharp": ", sharp focus, high resolution",
+            "Fooocus Masterpiece": ", masterpiece, best quality, award winning",
+        }
+        
+        selected_modifiers = [style_modifiers[style] for style in style_selections if style in style_modifiers]
+        processed_prompt = prompt + " ".join(selected_modifiers)
+        
+        return processed_prompt
+
+# Initialize the generator
+generator = FooocusGenerator()
+
+# Create the Gradio interface
+with gr.Blocks(title="Fooocus Web", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🎨 Fooocus Web")
+    gr.Markdown("Generate high-quality images with advanced controls")
+    
+    with gr.Row():
+        with gr.Column():
+            # Input components
+            prompt = gr.Textbox(
+                label="Prompt",
+                placeholder="Enter your image description here...",
+                info="Be specific and descriptive for better results"
+            )
+            negative_prompt = gr.Textbox(
+                label="Negative Prompt",
+                placeholder="What you don't want in the image...",
+                info="Specify unwanted elements",
+                value="ugly, blurry, low quality, distorted, deformed"
+            )
+            
+            with gr.Row():
+                style_selections = gr.CheckboxGroup(
+                    choices=["Fooocus V2", "Fooocus Enhance", "Fooocus Sharp", "Fooocus Masterpiece"],
+                    label="Style Selections",
+                    value=["Fooocus V2"]
+                )
+            
+            with gr.Row():
+                performance_selection = gr.Radio(
+                    choices=["Speed", "Quality", "Extreme Speed"],
+                    label="Performance",
+                    value="Quality"
+                )
+                
+                aspect_ratios_selection = gr.Radio(
+                    choices=["Square", "Portrait", "Landscape"],
+                    label="Aspect Ratio",
+                    value="Square"
+                )
+            
+            with gr.Row():
+                image_number = gr.Slider(
+                    minimum=1,
+                    maximum=32,
+                    value=1,
+                    step=1,
+                    label="Number of Images"
+                )
+                
+                image_seed = gr.Slider(
+                    minimum=-1,
+                    maximum=2147483647,
+                    step=1,
+                    value=-1,
+                    label="Seed (-1 for random)"
+                )
+            
+            with gr.Row():
+                sharpness = gr.Slider(
+                    minimum=0.0,
+                    maximum=30.0,
+                    value=2.0,
+                    step=0.1,
+                    label="Sharpness"
+                )
+                
+                guidance_scale = gr.Slider(
+                    minimum=1.0,
+                    maximum=20.0,
+                    value=7.5,
+                    step=0.1,
+                    label="Guidance Scale"
+                )
+            
+            with gr.Row():
+                base_model_name = gr.Dropdown(
+                    choices=["SDXL 1.0"],
+                    label="Base Model",
+                    value="SDXL 1.0"
+                )
+                
+                refiner_model_name = gr.Dropdown(
+                    choices=["SDXL Refiner"],
+                    label="Refiner",
+                    value="SDXL Refiner"
+                )
+            
+            generate_btn = gr.Button("🎨 Generate", variant="primary")
+        
+        with gr.Column():
+            # Output components
+            output_image = gr.Image(label="Generated Image", type="pil")
+            
+    # Connect the interface
+    generate_btn.click(
+        fn=generator.generate_image,
+        inputs=[
+            prompt,
+            negative_prompt,
+            style_selections,
+            performance_selection,
+            aspect_ratios_selection,
+            image_number,
+            image_seed,
+            sharpness,
+            guidance_scale,
+            base_model_name,
+            refiner_model_name
+        ],
+        outputs=output_image
+    )
+
+if __name__ == "__main__":
+    demo.launch(share=True)

requirements.txt

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+torch==2.2.1
+transformers>=4.36.2
+accelerate==0.25.0
+safetensors==0.4.1
+gradio==4.19.2
+diffusers==0.24.0
+opencv-python>=4.8.1.78
+einops>=0.7.0
+pytorch_lightning>=2.1.3
+omegaconf>=2.3.0
+peft>=0.7.1
+xformers>=0.0.23.post1
+triton>=2.1.0
+compel>=2.0.2